Zheng Xu - Google Scholar Citations

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	All	Since 2015
Citations	1106	1084
h-index	17	17
i10-index	18	18

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Co-authors

Tom GoldsteinPerotto Associate Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Christoph StuderAssociate Professor at Cornell University and Cornell Tech – VLSI Information Processing GroupVerified email at cornell.edu
Gavin TaylorUS Naval AcademyVerified email at usna.edu
Hao LiAmazon Web ServicesVerified email at amazon.com
Mario A. T. FigueiredoInstituto de Telecomunicações; Instituto Superior Técnico, Universidade de Lisboa, PortugalVerified email at ist.utl.pt
Soham DeDeepMindVerified email at google.com
Dong Xu, IEEE Fellow, Chair in Comp...University of SydneyVerified email at sydney.edu.au
Wen LiData Intelligence Group, UESTCVerified email at uestc.edu.cn
Xiaoming YuanThe University of Hong KongVerified email at hku.hk
Louiqa RaschidProfessor, University of MarylandVerified email at umiacs.umd.edu
Xitong YANGGraduate student of Computer Science, Univerisity of Maryland, College ParkVerified email at cs.umd.edu
John P. DickersonAssistant Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Ali ShafahiGraduate Research Assistant, University of MarylandVerified email at umd.edu
Larry DavisProfessor of Computer Science, University of MarylandVerified email at cs.umd.edu
Mahyar NajibiUniversity of MarylandVerified email at cs.umd.edu
Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHVerified email at ethz.ch
Dengxin DaiETH ZurichVerified email at ee.ethz.ch
Li NiuShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Xue LiUniversity of Maryland, College ParkVerified email at umd.edu
Yen-Chang HsuGeorgia Institute of TechnologyVerified email at gatech.edu

Zheng Xu

Google Research

Verified email at cs.umd.edu - Homepage

Machine Learning Optimization Computer Vision Multimedia Data Mining


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Visualizing the loss landscape of neural nets H Li, Z Xu, G Taylor, C Studer, T Goldstein Advances in Neural Information Processing Systems, 6391-6401, 2018	276	2018
Training neural networks without gradients: A scalable ADMM approach G Taylor, R Burmeister, Z Xu, B Singh, A Patel, T Goldstein International Conference on Machine Learning (ICML), 2722-2731, 2016	133	2016
Exploiting Low-Rank Structure from Latent Domains for Domain Generalization Z Xu, W Li, L Niu, D Xu European Conference on Computer Vision (ECCV), 628-643, 2014	91	2014
Training Quantized Nets: A Deeper Understanding H Li, S De, Z Xu, C Studer, H Samet, T Goldstein Conference on Neural Information Processing Systems (NIPS), 2017	76	2017
Adaptive ADMM with Spectral Penalty Parameter Selection Z Xu, MAT Figueiredo, T Goldstein International Conference on Artificial Intelligence and Statistics (AISTATS), 2017	53	2017
Adversarial Training for Free! A Shafahi, M Najibi, A Ghiasi, Z Xu, J Dickerson, C Studer, LS Davis, ... Conference on Neural Information Processing Systems (NeurIPS), 2019	49	2019
Mining Visualness Z Xu, XJ Wang, CW Chen IEEE International Conference on Multimedia and Expo (ICME), 2013	49*	2013
Domain Generalization and Adaptation using Low Rank Exemplar SVMs W Li, Z Xu, D Xu, D Dai, LV Gool IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017	47	2017
Towards Perceptual Image Dehazing by Physics-based Disentanglement and Adversarial Training X Yang, Z Xu, J Luo AAAI Conference on Artificial Intelligence (AAAI), 2018	39	2018
Advances and Open Problems in Federated Learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 2019	35	2019
Stabilizing Adversarial Nets With Prediction Methods A Yadav, S Shah, Z Xu, D Jacobs, T Goldstein International Conference on Learning Representations (ICLR), 2018	35	2018
Towards indexing representative images on the web XJ Wang, Z Xu, L Zhang, C Liu, Y Rui Proceedings of the 20th ACM international conference on Multimedia, 1229-1238, 2012	33	2012
Adaptive Consensus ADMM for Distributed Optimization Z Xu, G Taylor, H Li, M Figueiredo, X Yuan, T Goldstein International Conference on Machine Learning (ICML), 2017	28	2017
Training Student Networks for Acceleration with Conditional Adversarial Networks Z Xu, YC Hsu, J Huang British Machine Vision Conference (BMVC), 2018	24*	2018
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks Z Xu, YC Hsu, J Huang arXiv preprint arXiv:1709.00513, 2017	24	2017
An Empirical Study of ADMM for Nonconvex Problems Z Xu, S De, MAT Figueiredo, C Studer, T Goldstein NIPS workshop on nonconvex optimization, 2016	22	2016
Universal Adversarial Training A Shafahi, M Najibi, Z Xu, J Dickerson, LS Davis, T Goldstein AAAI Conference on Artificial Intelligence (AAAI), 2020	20	2020
Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation Z Xu, M Figueiredo, X Yuan, C Studer, T Goldstein IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017	19	2017
Strong Baseline for Single Image Dehazing with Deep Features and Instance Normalization Z Xu, X Yang, X Li, X Sun British Machine Vision Conference (BMVC), 2018	15*	2018
Exploiting Lists of Names for Named Entity Identification of Financial Institutions from Unstructured Documents Z Xu, D Burdick, L Raschid arXiv preprint arXiv:1602.04427, 2016	9	2016

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